MCScheduling 1.0
Set of Algorithms for Solving Mixed-Criticality Scheduling
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MCScheduling.ClairvoyantEDF | Contains the algorithm to solve mixed-criticality scheduling problems that is an adaptation of a clairvoyant non-preemptive scheduling algorithm by Cecilia Ekelin |
MCScheduling.GeneticAlgorithm | Contains the implementation of a (generic) genetic algorithm that may be used to solve different kind of optimization problems |
MCScheduling.MixedCriticality | Contains the representation of Mixed-Criticality Job, Mixed-Criticality Instance, several methods for their random generation, and mainly few algorithms to solve Mixed-Criticality Scheduling Problem |
MCScheduling.MixedCriticality.CEDF | Contains the implementation of a mixed-criticality solver based on the clairvoyant non-preemptive earliest deadline first algorithm |
MCScheduling.MixedCriticality.DP | Contains the implementation of a mixed-criticality solver based on the dynamic programming algorithm (similar to the one solving the traveling salesman problem) |
MCScheduling.MixedCriticality.GA | Contains the implementation of a mixed-criticality solver based on the genetic algorithm |
MCScheduling.MixedCriticality.MIP | Contains the implementation of a mixed-criticality solver based on the branch and bound algorithm provided by Gurobi 4.5 library |
MCScheduling.MixedCriticality.SA | Contains the implementation of a mixed-criticality solver based on the simulated annealing algorithm |
MCScheduling.SimulatedAnnealing | Contains the implementation of a (generic) simulated annealing algorithm that may be used to solve different kind of optimization problems |
MCScheduling.Utils | Contains two pseudo-random number generator implementations; one with uniform distribution (based on famous Mersenne Twister) and the other one with exponential distribution |